Referenced Items are not available for this document.
Most techniques for segmentation of magnetic resonance images of the brain are extremely time consuming and/or require extensive user interaction. An automated segmentation procedure is presented, whereby the fuzzy c-means classification results are used to train a feedforward neural network. The cascade correlation algorithm is used to optimize the network training process. After applying a brain-extraction technique, the segmented images are then used for rendering computer-generated images of the brain's surface. Experimental results using real, 3D magnetic resonance images are presented, demonstrating the performance of the segmentation as well as the final surface rendering
Published in:
Neural Networks, 1995. Proceedings., IEEE International Conference on
(Volume:5
)
Date of Conference: Nov/Dec 1995
- Page(s):
- 2190 - 2195 vol.5
- Meeting Date :
- 27 Nov 1995-01 Dec 1995
- Print ISBN:
- 0-7803-2768-3
- INSPEC Accession Number:
- 5274591
- Conference Location :
- Perth, WA
- Digital Object Identifier :
- 10.1109/ICNN.1995.487700
- Product Type:
- Conference Publications
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